Authors 
Tang, Patrick Y. H

Issue Date 
1993

Summary 
Sigmadelta modulation can be used to model the waveforrn coding process of biological neurons. The discretetime model can greatly simplify the analysis that are nontrivial with traditional continuous time models formulated with differential equations. In the σδ modulation neuronal model, we made observations that the neural information is transmitted and received reliably within the neural network due to the noise shaping and 'dithering' inherent in biological neurons. Aside from the analytical aspect, the model is also a good candidate for VLSI implementations. Sigmadelta neural networks have the same circuit complexity as the pulse coded neural networks. Sigmadelta neural networks is thus an efficient and feasible candidate on large scale implementation of silicon neural systems. 
Note 
Thesis (M.Phil.)Hong Kong University of Science and Technology, 1993 
Subjects 

Language 
English

Format 
Thesis 
Access 
